Search results for: classification of matter

Authors: Y. H. Wu, Ji-Yuan Lin, Yu-Ming Liou

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This study aims to set up the landslide susceptibility map of County Route 89 at Ren-Ai Township in Nantou County using the Instability Index Method and Logistic regression. Seven susceptibility factors including Slope Angle, Aspect, Elevation, Distance to fold, Distance to River, Distance to Road and Accumulated Rainfall were obtained by GIS based on the Typhoon Toraji landslide area identified by Industrial Technology Research Institute in 2001. To calculate the landslide percentage of each factor and acquire the weight and grade the grid by means of Instability Index Method. In this study, landslide susceptibility can be classified into four grades: high, medium high, medium low and low, in order to determine the advantages and disadvantages of the two models. The precision of this model is verified by classification error matrix and SRC curve. These results suggest that the logistic regression model is a preferred method than instability index in the assessment of landslide susceptibility. It is suitable for the landslide prediction and precaution in this area in the future.

Keywords: instability index method, logistic regression, landslide susceptibility, SRC curve

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Authors: Mikhail Zarechnev, Bora I. Kumova

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A syllogism is a deductive inference scheme used to derive a conclusion from a set of premises. In a categorical syllogisms, there are only two premises and every premise and conclusion is given in form of a quantified relationship between two objects. The different order of objects in premises give classification known as figures. We have shown that the ordered combinations of 3 generalized quantifiers with certain figure provide in total of 108 syllogistic moods which can be considered as different inference rules. The classical syllogistic system allows to model human thought and reasoning with syllogistic structures always attracted the attention of cognitive scientists. Since automated reasoning is considered as part of learning subsystem of AI agents, syllogistic system can be applied for this approach. Another application of syllogistic system is related to inference mechanisms on the Semantic Web applications. In this paper we proposed the mathematical model and algorithm for syllogistic reasoning. Also the model of iterative syllogistic reasoning in case of continuous flows of incoming data based on case–based reasoning and possible applications of proposed system were discussed.

Keywords: categorical syllogism, case-based reasoning, cognitive architecture, inference on the semantic web, syllogistic reasoning

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Authors: Mohd Ridzwan Yaakub, Muhammad Iqbal Abu Latiffi

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Online business has become popular recently due to the massive amount of information and medium available on the Internet. This has resulted in the huge number of reviews where the consumers share their opinion, criticisms, and satisfaction on the products they have purchased on the websites or the social media such as Facebook and Twitter. However, to analyze customer’s behavior has become very important for organizations to find new market trends and insights. The reviews from the websites or the social media are in structured and unstructured data that need a sentiment analysis approach in analyzing customer’s review. In this article, techniques used in will be defined. Definition of the ontology and description of its possible usage in sentiment analysis will be defined. It will lead to empirical research that related to mobile phones used in research and the ontology used in the experiment. The researcher also will explore the role of preprocessing data and feature selection methodology. As the result, ontology-based approach in sentiment analysis can help in achieving high accuracy for the classification task.

Keywords: feature selection, ontology, opinion, preprocessing data, sentiment analysis

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Authors: Jamal Ahmed Hama Kareem, Noraini Abu Talib

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The purpose of this paper is to explore the literature on 5S and Total Productive Maintenance (TPM) and the benefits that are to be derived from their implementation. It also seeks to highlight the main phases for implementing both the 5S and the TPM successfully, along with highlighting aspects that are needed for successful implementation of these two techniques simultaneously in the contemporary manufacturing scenario. The literature on classification of 5S and TPM has so far been very limited. The paper reviews a large number of papers in this field and presents the overview of several of implementation practices of 5S and TPM, and the benefits that can be achieved by the implementation of 5S and TPM as a one system by industrial organizations globally. The paper systematically categorizes the published literature and reveals important issues that influence the successful implementation of 5S and TPM in organizations to improve production effectiveness for competitiveness. Further, the paper also highlights various phases suggested by researchers and practitioners, which ensure smooth and effective implementation of the 5S and TPM in industrial organizations. In the end, study puts forth propositions based on the model of the study after extensive review of literature. The paper will be useful to researchers, maintenance professionals and other concerned officials with improving the performance of production processes effectiveness in industrial organizations.

Keywords: 5S, Total Productive Maintenance (TPM), phases of implementation of 5S and TPM, industrial organizations

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Authors: Sean Paulsen, Michael Casey

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In this work we present a self-supervised pretraining framework for transformers on functional Magnetic Resonance Imaging (fMRI) data. First, we pretrain our architecture on two self-supervised tasks simultaneously to teach the model a general understanding of the temporal and spatial dynamics of human auditory cortex during music listening. Our pretraining results are the first to suggest a synergistic effect of multitask training on fMRI data. Second, we finetune the pretrained models and train additional fresh models on a supervised fMRI classification task. We observe significantly improved accuracy on held-out runs with the finetuned models, which demonstrates the ability of our pretraining tasks to facilitate transfer learning. This work contributes to the growing body of literature on transformer architectures for pretraining and transfer learning with fMRI data, and serves as a proof of concept for our pretraining tasks and multitask pretraining on fMRI data.

Keywords: transfer learning, fMRI, self-supervised, brain decoding, transformer, multitask training

Procedia PDF Downloads 87

Authors: Meenakshi Barsaul Chauhan, Aastha Chauhan, Shilpa Hurmade, Rajeev Sen, Jyotsna Sen, Monika Dalal

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Introduction: Ovarian masses are common forms of neoplasm in women and represent 2/3rd of gynaecological malignancies. A pre-operative suggestion of malignancy can guide the gynecologist to refer women with suspected pelvic mass to a gynecological oncologist for appropriate therapy and optimized treatment, which can improve survival. In the younger age group preoperative differentiation into benign or malignant pathology can decide for conservative or radical surgery. Imaging modalities have a definite role in establishing the diagnosis. By using International Ovarian Tumor Analysis (IOTA) classification with sonography, costly radiological methods like Magnetic Resonance Imaging (MRI) / computed tomography (CT) scan can be reduced, especially in developing countries like India. Thus, this study is being undertaken to evaluate the role of clinical methods and sonography for diagnosis of the nature of the ovarian tumor. Material And Methods: This prospective observational study was conducted on 40 patients presenting with ovarian masses, in the Department of Obstetrics and Gynaecology, at a tertiary care center in northern India. Functional cysts were excluded. Ultrasonography and color Doppler were performed on all the cases.IOTA rules were applied, which take into account locularity, size, presence of solid components, acoustic shadow, dopper flow etc . Magnetic Resonance Imaging (MRI) / computed tomography (CT) scans abdomen and pelvis were done in cases where sonography was inconclusive. In inoperable cases, Fine needle aspiration cytology (FNAC) was done. The histopathology report after surgery and cytology report after FNAC was correlated statistically with the pre-operative diagnosis made clinically and sonographically using IOTA rules. Statistical Analysis: Descriptive measures were analyzed by using mean and standard deviation and the Student t-test was applied and the proportion was analyzed by applying the chi-square test. Inferential measures were analyzed by sensitivity, specificity, negative predictive value, and positive predictive value. Results: Provisional diagnosis of the benign tumor was made in 16(42.5%) and of the malignant tumor was made in 24(57.5%) patients on the basis of clinical findings. With IOTA simple rules on sonography, 15(37.5%) were found to be benign, while 23 (57.5%) were found to be malignant and findings were inconclusive in 2 patients (5%). FNAC/Histopathology reported that benign ovarian tumors were 14 (35%) and 26(65%) were malignant, which was taken as the gold standard. The clinical finding alone was found to have a sensitivity of 66.6% and a specificity of 90.9%. USG alone had a sensitivity of 86% and a specificity of 80%. When clinical findings and IOTA simple rules of sonography were combined (excluding inconclusive masses), the sensitivity and specificity were 83.3% and 92.3%, respectively. While including inconclusive masses, sensitivity came out to be 91.6% and specificity was 89.2. Conclusion: IOTA's simple sonography rules are highly sensitive and specific in the prediction of ovarian malignancy and also easy to use and easily reproducible. Thus, combining clinical examination with USG will help in the better management of patients in terms of time, cost and better prognosis. This will also avoid the need for costlier modalities like CT, and MRI.

Keywords: benign, international ovarian tumor analysis classification, malignant, ovarian tumours, sonography

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Authors: Wizna, Helmi Muis, Hafil Abbas

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An experiment was conducted to improve the nutrient value of sago pith (Metroxylon sago Rottb) supplemented with Zn, Sulfur and urea through fermentation by using cellulolytic bacteria (Bacillus amyloliquefaciens) as inoculums. The experiment was determination of the optimum dose combination (dosage of Zn, S and urea) for sago pith fermentation based on nutrient quality and quantity of these fermented products. The study was conducted in experimental method, using the completely randomized design in factorial with 3 treatments consist of: factor A (Dose of urea: A1 = 2.0%, A2 = 3.0%), factor B (Dose of S: B1 = 0.2%, B2 = 0.4%) and factor C (Dose of Zn: C1 = 0.0025%, C2 = 0.005%). Results of study showed that optimum condition for fermentation process of sago pith with B. amyloliquefaciens caused a change of nutrient content was obtained at urea (3%), S (0,2%), and Zn (0,0025%). This fermentation process was able to increase amino acid average, reduce crude fiber content by 67% and increase crude protein by 433%, which made the nutritional value of the product based on dry matter was 18.22% crude protein, 12.42% crude fiber, 2525 Kcal/kg metabolic energy and 65.73% nitrogen retention.

Keywords: fermentation, sago pith, sulfur, Zn, urea, Bacillus amyloliquefaciens

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Authors: Heba Elbibas, Esra Gnijeewa, Zedan Hatush

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This paper presents research on occupational safety in construction projects, where the importance of safety management in projects was studied, including the preparation of a safety plan and program for each project and the identification of the responsibilities of each party to the contract. The research consists of two parts: 1-Field visits: which were field visits to three construction projects, including building projects, road projects, and tower installation. The safety level of these projects was evaluated through a checklist that includes the most important safety elements in terms of the application of these items in the projects. 2-Preparation of a questionnaire: which included supervisors and engineers and aimed to determine the level of awareness and commitment of different project categories to safety standards. The results showed the following: i) There is a moderate occupational safety policy. ii) The preparation and storage of maintenance reports are not fully complied with. iii) There is a moderate level of training on occupational safety for project workers. iv) The company does not impose penalties on safety violators permanently. v) There is a moderate policy for equipment and machinery safety. vi) Self-injuries occur due to (fatigue, lack of attention, deliberate error, and emotional factors), with a rate of 82.4%.

Keywords: management, safety, occupational safety, classification

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Authors: Sangguk Ahn, Youngyu Kim, Jaheon Gu, Gyoutae Park

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In this paper, we developed a dual gas leak instrument to detect Hydrocarbon (HC) and Monoxide (CO) gases. To two kinds of gases, it is necessary to design compact structure for sensors. And then it is important to draw sensing circuits such as measuring, amplifying and filtering. After that, it should be well programmed with robust, systematic and module coding methods. In center of them, improvement of accuracy and initial response time are a matter of vital importance. To manufacture distinguished gas leak detector, we applied intrinsically safe explosion-proof structure to lithium ion battery, main circuits, a pump with motor, color LCD interfaces and sensing circuits. On software, to enhance measuring accuracy we used numerical analysis such as Lagrange and Neville interpolation. Performance test result is conducted by using standard Methane with seven different concentrations with three other products. We want raise risk prevention and efficiency of gas safe management through distributing to the field of gas safety. Acknowledgment: This study was supported by Small and Medium Business Administration under the research theme of ‘Commercialized Development of a portable intrinsically safe explosion-proof type dual gas leak detector’, (task number S2456036).

Keywords: gas leak, dual gas detector, intrinsically safe, explosion proof

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Authors: Daniele Contini, Antonio Donateo, Andrea Gambaro, Athanasios Argiriou, Dimitrios Melas, Daniela Cesari, Anastasia Poupkou, Athanasios Karagiannidis, Apostolos Tsakis, Eva Merico, Rita Cesari, Adelaide Dinoi

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Emissions of atmospheric pollutants from ships and harbour activities are a growing concern at International level given their potential impacts on air quality and climate. These close-to-land emissions have potential impact on local communities in terms of air quality and health. Recent studies show that the impact of maritime traffic to atmospheric particulate matter concentrations in several coastal urban areas is comparable with the impact of road traffic of a medium size town. However, several different approaches have been used for these estimates making difficult a direct comparison of results. In this work an integrated approach based on emission inventories and dedicated measurement campaigns has been applied to give a comparable estimate of the impact of maritime traffic to PM2.5 and particle number concentrations in three major harbours of the Adriatic/Ionian Seas. The influences of local meteorology and of the logistic layout of the harbours are discussed.

Keywords: ship emissions, PM2.5, particle number concentrations, impact of shipping to atmospheric aerosol

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Authors: Naveed Ghani, Samreen Javed

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In today’s heterogeneous network environment, there is a growing demand for distrust clients to jointly execute secure network to prevent from malicious attacks as the defining task of propagating malicious code is to locate new targets to attack. Residual risk is always there no matter what solutions are implemented or whet so ever security methodology or standards being adapted. Security is the first and crucial phase in the field of Computer Science. The main aim of the Computer Security is gathering of information with secure network. No one need wonder what all that malware is trying to do: It's trying to steal money through data theft, bank transfers, stolen passwords, or swiped identities. From there, with the help of our survey we learn about the importance of white listing, antimalware programs, security patches, log files, honey pots, and more used in banks for financial data protection but there’s also a need of implementing the IPV6 tunneling with Crypto data transformation according to the requirements of new technology to prevent the organization from new Malware attacks and crafting of its own messages and sending them to the target. In this paper the writer has given the idea of implementing IPV6 Tunneling Secessions on private data transmission from financial organizations whose secrecy needed to be safeguarded.

Keywords: network worms, malware infection propagating malicious code, virus, security, VPN

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Authors: Dim En Nyaung, Thin Lai Lai Thein

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Due to the rapid increase of Internet, web opinion sources dynamically emerge which is useful for both potential customers and product manufacturers for prediction and decision purposes. These are the user generated contents written in natural languages and are unstructured-free-texts scheme. Therefore, opinion mining techniques become popular to automatically process customer reviews for extracting product features and user opinions expressed over them. Since customer reviews may contain both opinionated and factual sentences, a supervised machine learning technique applies for subjectivity classification to improve the mining performance. In this paper, we dedicate our work is the task of opinion summarization. Therefore, product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the identification of semantic relationships. The polarity and numeric score of all the features are determined by Senti-WordNet Lexicon. The problem of opinion summarization refers how to relate the opinion words with respect to a certain feature. Probabilistic based model of supervised learning will improve the result that is more flexible and effective.

Keywords: opinion mining, opinion summarization, sentiment analysis, text mining

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Authors: Carlo Gadingan

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Swardspeak, as a language, highlights the exclusive identity of the Filipino gay men and the oppression they are confronted in the society. This paper presents a morphological analysis of swardspeak in the Philippines. Specifically, it aims to find out the common morphological processes involved in the construction of codes that may unmask the nature of swardspeak as a language. 30 purposively selected expert users of swardspeak from Luzon, Visayas, and Mindanao were asked to codify 30 natural words through the Facebook Messenger application. The results of the structural analysis affirm that swardspeak follows no specific rules revealing complicated combinations of clipping/stylized clipping, borrowing, connotation through images, connotation through actions, connotation through sounds, affixation, repetition, substitution, and simple reversal. Moreover, it was also found out that most of these word formation processes occur in all word classes which indicate that swardspeak is very unpredictable. Although different codes are used for the same words, there are still codes that are really common to all homosexuals and these are Chaka (ugly), Crayola (cry), and Aida (referring to a person with AIDS). Hence, the prevailing word formation processes explored may be termed as observed time-specific patterns because the codes documented in this study may turn obsolete and may be replaced with novel ones in a matter of weeks to month, knowing the creativity of homosexuals and the multiplicity of societal resources which can be used to make the codes more opaque and more confusing for non-homosexuals.

Keywords: codes, homosexuals, morphological processes, swardspeak

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Authors: Omid Khabiri, Maryam Ghavami

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Buildings designed and built as high performance, sustainable or green are the vanguard in a movement to make buildings more energy efficient and less environmentally harmful. Although Heating, Ventilating, and Air Conditioning (HVAC) systems offer many opportunities for recovery and re-use of thermal energy; however, the amount of energy used annually by these systems typically ranges from 40 to 60 percent of the overall energy consumption in a building, depending on the building design, function, condition, climate, and the use of renewable energy strategies. HVAC systems may also damage the environment by unnecessary use of non-renewable energy sources, which contribute to environmental pollution, and by creating noise and discharge of contaminated water and air containing chemicals, lubricating oils, refrigerants, heat transfer fluids, and particulate (gases matter). In fact, HVAC systems will significantly impact how “green” a building is, where an efficient HVAC system design can result in considerable energy, emissions and cost savings as well as providing increased user thermal comfort. This paper presents the basic concepts of green building design and discusses the role of efficient HVAC system and practical strategies for ensuring high performance sustainable buildings in design and operation.

Keywords: green building, hvac system, design strategies, high-performance equipment, efficient technologies

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Authors: Tarik Ouslimane, Abdenour Lami, Salaheddine Aoudj, Mouna Hecini, Ouahiba Bouchelaghem, Nadjib Drouiche

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Slurry waste is a byproduct generated from the slicing process of multi-crystalline silicon ingots. This waste can be used as a secondary resource to recover high purity silicon which has a great economic value. From the management perspective, the ever increasing generation of kerf slurry waste loss leads to significant challenges for the photovoltaic industry due to the current low use of slurry waste for silicon recovery. Slurry waste, in most cases, contains silicon, silicon carbide, metal fragments and mineral-oil-based or glycol-based slurry vehicle. As a result, of the global scarcity of high purity silicon supply, the high purity silicon content in slurry has increasingly attracted interest for research. This paper presents a critical overview of the current techniques employed for high purity silicon recovery from kerf slurry waste. Hydrometallurgy is continuously a matter of study and research. However, in this review paper, several new techniques about the process of high purity silicon recovery from slurry waste are introduced. The purpose of the information presented is to improve the development of a clean and effective recovery process of high purity silicon from slurry waste.

Keywords: Kerf-loss, slurry waste, silicon carbide, silicon recovery, photovoltaic, high purity silicon, polyethylen glycol

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Authors: Z. M. Iqbal, M. Abdullah, K. Javed, M. A. Jabbar, A. Haque, M. Saadullah, F. Shahzad

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The current study was conducted to set the appropriate concentrate level for Nili-Ravi buffalo heifers. Twenty seven buffalo heifers were randomly divided into three different groups A, B and C having nine animals in each group. All the heifers were given free access to chopped green fodder and fresh water. In addition, heifers of group A, B and C were given concentrate at the rate of 0.5%, 1% and 1.5% of their body weight. The average daily dry matter intake was 2.69, 3.06 and 3.83 kg with average daily gain of 456.09, 398.56 and 515.87 gm in group A, B and C, respectively. The feed conversion ratio of heifers of these groups was 5.89, 7.74 and 7.52, respectively. There was non-significant (P>0.05) difference in the body measurements (height at wither, body length and heart girth), final body condition and scoring and blood serum (glucose, total protein and cholesterol) of heifers of all the three groups. The results of current study shows that there is non-significant (P>0.05) difference in the growth rate of Nili-Ravi heifers at varying levels of concentrate so, it is cost effective to raise 6-8 month calves by offering concentrate at the rate of 0.5% body weight along with free access of green fodder.

Keywords: concentrate level, buffalo heifer, body measurement, green fodder

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Authors: Peng Wang, Tigang Jiang

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The computer based lip reading method of different languages cannot be universal. At present, for the research of Chinese lip reading, whether the work on data sets or recognition algorithms, is far from mature. In this paper, we study the Chinese lipreading method based on machine learning, and propose a Chinese Sentence-level lip-reading network (CNLipNet) model which consists of spatio-temporal convolutional neural network(CNN), recurrent neural network(RNN) and Connectionist Temporal Classification (CTC) loss function. This model can map variable-length sequence of video frames to Chinese Pinyin sequence and is trained end-to-end. More over, We create CNLRS, a Chinese Lipreading Dataset, which contains 5948 samples and can be shared through github. The evaluation of CNLipNet on this dataset yielded a 41% word correct rate and a 70.6% character correct rate. This evaluation result is far superior to the professional human lip readers, indicating that CNLipNet performs well in lipreading.

Keywords: lipreading, machine learning, spatio-temporal, convolutional neural network, recurrent neural network

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Authors: Ajish K. Abraham

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Hearing aid is the most fundamental technology employed towards rehabilitation of persons with sensory neural hearing impairment. Hearing in noise is still a matter of major concern for many hearing aid users and thus continues to be a challenging issue for the hearing aid designers. Several techniques are being currently used to enhance the speech at the hearing aid output. Most of these techniques, when implemented, result in reduction of intelligibility of the speech signal. Thus the dissatisfaction of the hearing aid user towards comprehending the desired speech amidst noise is prevailing. Multichannel Wiener Filter is widely implemented in binaural hearing aid technology for noise reduction. In this study, Wiener filter based noise reduction approach is experimented for a single microphone based hearing aid set up. This method checks the status of the input speech signal in each frequency band and then selects the relevant noise reduction procedure. Results showed that the Wiener filter based algorithm is capable of enhancing speech even when the input acoustic signal has a very low Signal to Noise Ratio (SNR). Performance of the algorithm was compared with other similar algorithms on the basis of improvement in intelligibility and SNR of the output, at different SNR levels of the input speech. Wiener filter based algorithm provided significant improvement in SNR and intelligibility compared to other techniques.

Keywords: hearing aid output speech, noise reduction, SNR improvement, Wiener filter, speech enhancement

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Authors: Hadriana Bansi, Elizabeth Wina, Toto Toharmat

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Acacia villosa is thornless shrub legume which contents high crude protein. However, the utilization of A. villosa as ruminant feed is limited by its secondary compounds. The aim of this article is to find out the maximum of substitution A. villosa in sheep ration. The nutritional evaluation consisted of in vitro two stages, in vivo, and in vitro gas production trials. The secondary compounds of A. villosa also were analyzed. Evaluating digestibility of increasing level of substitution A. villosa replacing Pennisetum purpureum was using in vitro two stages. The substitution of 30% A. villosa was compared to 100% P. purpureum by in vitro gas production technique and in vivo digestibility. The results of two stages in vitro showed that total phenol, condensed tannin, and non-protein amino acid (NPAA) were high. Substitution 15% A. villosa reached the highest digestibility for both dry matter (DM) and crude protein (CP) which were 67% and 86% respectively, but it was shown that DM and CP digestibility of substitution 30% of A. villosa was still high which were 61.82% and 75-67% respectively. The pattern of gas production showed that first 8 hours total gas production substitution of 30% A. villosa was higher than 100% P. purpureum and declined after 10 hours incubation. In vivo trials showed that substitution of 30% A. villosa significantly increased CP intake, CP digestibility, and nitrogen retention. It can be concluded that substitution A. villosa until 30% still gave the good impact even though it has high secondary compounds.

Keywords: Acacia villosa, digestibility, gas production, secondary compounds

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Authors: Go Woon Kwak, Siyoung Jun, Soyun Maeng, Haeyoung Lee

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Entry is an education platform used in South Korea, created to help students learn to program, in which they can learn to code while playing. Using the online version of the entry, teachers can easily assign programming homework to the student and the students can make programs simply by linking programming blocks. However, the programs may be made by others, so that the authors of the programs should be identified. In this paper, as the first step toward author identification of entry programs, we present an artificial neural network based classification approach to identify genders of authors of a program written in an entry. A neural network has been trained from labeled training data that we have collected. Our result in progress, although preliminary, shows that the proposed approach could be feasible to be applied to the online version of entry for gender identification of authors. As future work, we will first use a machine learning technique for age identification of entry programs, which would be the second step toward the author identification.

Keywords: artificial intelligence, author identification, deep neural network, gender identification, machine learning

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Authors: Mohd Moiz Khan, S. M. Mahajani, G. N. Jadhav

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Waste foundry sand (total clay content 15%) contains toxic heavy metals and particulate matter which make dumping of waste sand an environmental and health hazard. Disposal of waste foundry sand (WFS) remains one of the substantial challenges faced by Indian foundries nowadays. To cope up with this issue, the chemical method was used to reclaim WFS. A stirrer tank reactor was used for chemical reclamation. Experiments were performed to reduce the total clay content from 15% to as low as 0.9% in chemical reclamation. This method, although found to be effective for WFS reclamation, it may face a challenge due to the possibly high operating cost. Reclaimed sand was found to be satisfactory in terms of sand qualities such as total clay (0.9%), active clay (0.3%), acid demand value (ADV) (2.6%), loss on igniting (LOI) (3 %), grain fineness number (GFN) (56), and compressive strength (60 kPa). The experimental data generated on chemical reactor under different conditions is further used to optimize the design and operating parameters (rotation speed, sand to acidic solution ratio, acid concentration, temperature and time) for the best performance. The use of reclaimed sand within the foundry would improve the economics and efficiency of the process and reduce environmental concerns.

Keywords: chemical reclamation, clay content, environmental concerns, recycle, waste foundry sand

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Authors: Piyush Swami, Bijaya Ketan Panigrahi, Sneh Anand, Manvir Bhatia, Tapan Gandhi

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Visual inspection of electroencephalogram (EEG) signals to detect epileptic signals is very challenging and time-consuming task even for any expert neurophysiologist. This problem is most challenging in under-developed and developing countries due to shortage of skilled neurophysiologists. In the past, notable research efforts have gone in trying to automate the seizure detection process. However, due to high false alarm detections and complexity of the models developed so far, have vastly delimited their practical implementation. In this paper, we present a novel scheme for epileptic seizure detection using empirical mode decomposition technique. The intrinsic mode functions obtained were then used to calculate the standard deviations. This was followed by probability density based classifier to discriminate between non-ictal and ictal patterns in EEG signals. The model presented here demonstrated very high classification rates ( > 97%) without compromising the statistical performance. The computation timings for each testing phase were also very low ( < 0.029 s) which makes this model ideal for practical applications.

Keywords: electroencephalogram (EEG), epilepsy, ictal patterns, empirical mode decomposition

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Authors: Marieta Safta

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The separation and balance of state powers constitute the basis of the rule of law. Observance of this principle requires framing of public authorities within the limits of competence established by the Constitution and the law, as well as loyal cooperation between them. From this perspective, the attribution of the constitutional courts for settling legal conflicts of a constitutional nature is an important tool for correcting the tendencies of violation of these limits, as well as for identifying solutions for situations that do not find an explicit regulation in the constitutional texts. The present study analyzes the jurisprudence of the Constitutional Court of Romania in the field of legal conflicts of a constitutional nature, revealing, together with the presentation of conflict situations, the vulnerabilities of the constitutional reference texts. It is also highlighted the role of the constitutional courts in the evolution of constitutional law institutions, even in terms of defining and redefining the regime of the forms of government. The conclusion of the study, beyond the subject of legal conflicts of a constitutional nature, bears on the necessity, even more so in this matter, of the certainty of jurisdictional interpretation. This certainty cannot be achieved as long as the interpretation is not authoritative; consequently, the assurance of the effectiveness of constitutional justice constitute a key issue of the rule of law.

Keywords: legal conflicts of constitutional nature, the Constitutional Court of Romania, the separation and balance of powers in the state, the effectiveness of constitutional justice

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Authors: Shruti Jain

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During its independence struggle in the early 20th century, India witnessed trends of politicisation of various spiritual paths, one of them being that of Shaktism. Interestingly, Nietzsche’s teachings were being interpreted as being essentially the worship of Shakti. The present paper aims at investigating this claim and hence undertakes an intercultural archaeological excavation in the realm of the Goddess archetypes that Nietzsche’s work invokes. Ariadne is placed next to Radha, Baubo to Lajja Gauri, Medusa to Chhinnamasta, Hecate to Kali and Dhumavati and Athena to Sarawati. Indeed, the Eternal Feminine plays a vital role in Nietzsche’s writings. One might recall that Nietzsche even declared himself to be the first Psychologist of the Eternal Feminine. The present paper aims to illustrate how, the matter of the Eternal Feminine, like all other matters, is subjected to Nietzsche’s basic creative principle of transvaluation of values and new meaning making. In order to achieve this, Nietzsche applies what Heidegger calls a 'cross-wise striking-through' technique in his analysis of what can be termed as his engagement with Shaktism. Hence, not only is the mystical ascent and descent of the creative energy (Kundalini Shakti) dealt with under erasure in Thus Spake Zarathustra, but coincidentally also the Three Metamorphoses emerge as an instance of such an erasure, making the Devi invisible and yet not so invisible for an Indian reader.

Keywords: eternal feminine, Nietzsche and India, Shaktism, transvaluation of values

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Authors: Usman Qamar, Younus Javed

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Frequent pattern mining is the process of finding a pattern (a set of items, subsequences, substructures, etc.) that occurs frequently in a data set. It was proposed in the context of frequent itemsets and association rule mining. Frequent pattern mining is used to find inherent regularities in data. What products were often purchased together? Its applications include basket data analysis, cross-marketing, catalog design, sale campaign analysis, Web log (click stream) analysis, and DNA sequence analysis. However, one of the bottlenecks of frequent itemset mining is that as the data increase the amount of time and resources required to mining the data increases at an exponential rate. In this investigation a new algorithm is proposed which can be uses as a pre-processor for frequent itemset mining. FASTER (FeAture SelecTion using Entropy and Rough sets) is a hybrid pre-processor algorithm which utilizes entropy and rough-sets to carry out record reduction and feature (attribute) selection respectively. FASTER for frequent itemset mining can produce a speed up of 3.1 times when compared to original algorithm while maintaining an accuracy of 71%.

Keywords: rough-sets, classification, feature selection, entropy, outliers, frequent itemset mining

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Authors: Akane Uda, Ami Tabata, Mi An, Misa Komaki, Ryotaro Ito, Mayumi Inoue, Takehiro Sasai, Yusuke Kusano, Toshihiro Kato

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Early intervention is recommended for children with autism spectrum disorder (ASD), and an increasing number of children have received support and intervention before school age in recent years. In this study, we systematically reviewed preschool interventions focused on repetitive behaviors observed in children with ASD, which are often observed at younger ages. Inclusion criteria were as follows : (1) Child of preschool status (age ≤ 7 years) with a diagnosis of ASD (including autism, Asperger's, and pervasive developmental disorder) or a parent (caregiver) with a preschool child with ASD, (2) Physician-confirmed diagnosis of ASD (autism, Asperger's, and pervasive developmental disorder), (3) Interventional studies for repetitive behaviors, (4) Original articles published within the past 10 years (2012 or later), (5) Written in English and Japanese. Exclusion criteria were as follows: (1) Systematic reviews or meta-analyses, (2) Conference reports or books. We carefully scrutinized databases to remove duplicate references and used a two-step screening process to select papers. The primary screening included close scrutiny of titles and abstracts to exclude articles that did not meet the eligibility criteria. During the secondary screening, we carefully read the complete text to assess eligibility, which was double-checked by six members at the laboratory. Disagreements were resolved through consensus-based discussion. Our search yielded 304 papers, of which nine were included in the study. The level of evidence was as follows: three randomized controlled trials (level 2), four pre-post studies (level 4b), and two case reports (level 5). Seven articles selected for this study described the effectiveness of interventions. Interventions for repetitive behaviors in preschool children with ASD were categorized as five interventions that directly involved the child and four educational programs for caregivers and parents. Studies that directly intervened with children used early intensive intervention based on applied behavior analysis (Early Start Denver Model, Early Intensive Behavioral Intervention, and the Picture Exchange Communication System) and individualized education based on sensory integration. Educational interventions for caregivers included two methods; (a) education regarding combined methods and practices of applied behavior analysis in addition to classification and coping methods for repetitive behaviors, and (b) education regarding evaluation methods and practices based on children’s developmental milestones in play. With regard to the neurophysiological basis of repetitive behaviors, environmental factors are implicated as possible contributors. We assumed that applied behavior analysis was shown to be effective in reducing repetitive behaviors because analysis focused on the interaction between the individual and the environment. Additionally, with regard to educational interventions for caregivers, the intervention was shown to promote behavioral change in children based on the caregivers' understanding of the classification of repetitive behaviors and the children’s developmental milestones in play and adjustment of the person-environment context led to a reduction in repetitive behaviors.

Keywords: autism spectrum disorder, early intervention, repetitive behaviors, systematic review

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Authors: Xiaoxiao Li, Shuangcheng Jia, Qian Li

Abstract:

Keypoint detection has always been a challenge in the field of image recognition. This paper proposes a novelty keypoint detection method which is called Multi-Scale Feature Fusion Convolutional Network with Attention (MFFCNA). We verified that the multi-scale features with the attention mechanism module have better feature expression capability. The feature fusion between different scales makes the information that the network model can express more abundant, and the network is easier to converge. On our self-made street sign corner dataset, we validate the MFFCNA model with an accuracy of 97.8% and a recall of 81%, which are 5 and 8 percentage points higher than the HRNet network, respectively. On the COCO dataset, the AP is 71.9%, and the AR is 75.3%, which are 3 points and 2 points higher than HRNet, respectively. Extensive experiments show that our method has a remarkable improvement in the keypoint recognition tasks, and the recognition effect is better than the existing methods. Moreover, our method can be applied not only to keypoint detection but also to image classification and semantic segmentation with good generality.

Keywords: keypoint detection, feature fusion, attention, semantic segmentation

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Authors: Elihasridas, Rusmana Wijaya Setia Ninggrat

Abstract:

This research aims to study the utilization of ammoniated corn waste complete ration for substitution basal ration of natural grass in Bali cattle. Four treatments (complete feed ration consisted of: R1=40% natural grass + 60% concentrate (control), R2= 50% natural grass+50% concentrate, R3=60% natural grass+40% concentrate and R4=40% ammoniated corn waste+60% concentrate) were employed in this experiment. This experiment was arranged in a latin square design. Observed variables included dry matter intake (DMI), average daily gain and feed conversion. Data were analyzed by using the Analysis of Variance following a 4 x 4 Latin Square Design. The DMI for R1was 7,15kg/day which was significantly (P < 0,05) higher than R2 (6,32 kg/day) and R3(6,07 kg/day), but was not significantly different (P < 0,05) from R4 (7,01 kg/day). Average daily gain for R1(0,75 kg/day) which was significantly (P < 0,05) higher than R2(0,66 kg/day) and R3 (0,61 kg/day),but was not significantly different (P > 0,05) from R4(0,74 kg/day). Feed conversion was not significantly affected (P > 0,05) by ration. It was concluded that ammoniated corn waste complete ration (40% ammoniated corn waste + 60% concentrate) could be utilized for substitution natural grass basal ration.

Keywords: ammoniated corn waste, bali cattle, complete feed, daily gain

Procedia PDF Downloads 205

Authors: Seyedtaghi Mirmohammadi, Jamshid Yazdani, Syavash Etemadi Nejad

Abstract:

One of the main indoor air parameters in classrooms is dust pollution and it depends on the particle size and exposure duration. However, there is a lake of data about the exposure level to PM2.5 concentrations in rural area classrooms. The objective of the current study was exposure assessment for PM2.5 for students in the classrooms. One year monitoring was carried out for fifteen schools by time-series sampling to evaluate the indoor air PM2.5 in the rural district of Sari city, Iran. A hygrometer and thermometer were used to measure some psychrometric parameters (temperature, relative humidity, and wind speed) and Real-Time Dust Monitor, (MicroDust Pro, Casella, UK) was used to monitor particulate matters (PM2.5) concentration. The results show the mean indoor PM2.5 concentration in the studied classrooms was 135µg/m3. The regression model indicated that a positive correlation between indoor PM2.5 concentration and relative humidity, also with distance from city center and classroom size. Meanwhile, the regression model revealed that the indoor PM2.5 concentration, the relative humidity, and dry bulb temperature was significant at 0.05, 0.035, and 0.05 levels, respectively. A statistical predictive model was obtained from multiple regressions modeling for indoor PM2.5 concentration and indoor psychrometric parameters conditions.

Keywords: classrooms, concentration, humidity, particulate matters, regression

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Authors: Obiora E. Anisiji, Jeremiah L. Chukwuneke, Chinonso H. Achebe, Paul C. Okolie

Abstract:

This work developed a mathematical model of a biogas plant from a mechanistic point of view, for urban area clean energy requirement. It aimed at integrating thermodynamics; which deals with the direction in which a process occurs and Biochemical kinetics; which gives the understanding of the rates of biochemical reaction. The mathematical formulation of the proposed gas plant follows the fundamental principles of thermodynamics, and further analysis were accomplished to develop an algorithm for evaluating the plant performance preferably in terms of daily production capacity. In addition, the capacity of the plant is equally estimated for a given cycle of operation and presented in time histories. A nominal 1500m3 biogas plant was studied characteristically and its performance efficiency evaluated. It was observed that the rate of biogas production is essentially a function of enthalpy ratio, the reactor temperature, pH, substrate concentration, rate of degradation of the biomass, and the accumulation of matter in the system due to bacteria growth. The results of this study conform to a very large extent with reported empirical data of some existing plant and further model validations were conducted in line with classical records found in literature.

Keywords: anaerobic digestion, biogas plant, biogas production, bio-reactor, energy, fermentation, rate of production, temperature, therm

Procedia PDF Downloads 433